Optimizing Method of AVS2 Decoder for Mobile Terminal

With the popularity of mobile terminals and the increasing demand of video applications in mobile terminals, decoding speed of mobile terminal decoder becomes an important factor affecting video viewing perception. AVS is a series of standards formulated in accordance with international open rules to meet the needs of China’s audio and video industry. The software decoding speed of AVS2 (Second Generation of AVS) standard in mobile terminal is difficult to meet the requirements of real-time decoding of high-definition and ultra-high-definition video. In this paper, we study and implement a decoding optimization method using in Android – Selecting the sizes of \( 16 \times 16 \) and \( 32 \times 32 \) decoding units to reduce the computational complexity by intercepting certain frequency components during the procedure of IDCT (Inverse Discrete Cosine Transformation) at the decoder. With losing a small amount of image quality, this method can improve the decoding speed. Experiments show that this method can reduce the decoding time by 6%–9% in different resolution video.

[1]  Moncef Gabbouj,et al.  Sparse/DCT (S/DCT) Two-Layered Representation of Prediction Residuals for Video Coding , 2013, IEEE Transactions on Image Processing.

[2]  Jun Zhang,et al.  Depth based two-step disparity vector derivation for AVS2-3D , 2016, 2016 Visual Communications and Image Processing (VCIP).

[3]  Wen Gao,et al.  The second generation IEEE 1857 video coding standard , 2015, 2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP).

[4]  Lu Yu,et al.  Transform coding in AVS2 , 2014, 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).

[5]  Carl McCrosky,et al.  A fast hybrid DCT architecture supporting H.264, VC-1, MPEG-2, AVS and JPEG codecs , 2012, 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA).

[6]  Haigang Yang,et al.  Low Cost 1D DCT Core for Multiple Video Codec , 2016 .